Various transforms for digital signal processing are almost always used when digital images are being coded or processed. Such transforms include the discrete cosine transform, fast Fourier transform, various transforms based on wavelet theory, the Hadamard transform, and others. Digital images are often produced by a camera, and the images can take the form of still images or be composed into a series of images, that is, a video image.
Transform-based image processing can be computationally intensive. For that reason, enhancements on both hardware and software used for computations in transforms have been developed. For example, suitable approximations of transforms have been developed so that they are fast to compute on a processor. On the other hand, processor architectures have been developed so that a large number of similar computations can be efficiently computed—this is often the case with digital image processing. However, hardware architectures often need to be adapted for many purposes, and may not be optimized for any single purpose.
There is, therefore, a need for solutions that enable efficient computation in transform-based image processing.